The incentive / margin balance
Too high and the sale never happens. Too low and the margin disappears. The engine looks for the point in between.
Research concept · Fruit and vegetables
The right price,
at the right moment.
PriXmeur explores one question: can an independent greengrocer measure how their customers respond to price, and derive from it the price that holds the balance between the incentive to buy and the margin? The engine segments, estimates and proposes. It abstains when it is unsure. Nothing is deployed: what you see is a research prototype.
Behavioural segmentation Optimal price per segment Markdown as expiry nears
The stall first. The curve after.
AI engine · margin optimisation
Scenario · MarginSelected segment
Price-sensitive
Current price€3.70
Recommended price€3.55-4.0%
Estimated elasticity1.68
Estimated performance by price Margin Volume
Estimated margin +4.8%
Estimated revenue +2.1%
Estimated volume -1.9%
Artificial intelligence
The engine is an AI. You supervise it.
A statistical model fitted to your sales, which measures, proposes and justifies. It never publishes a price on its own initiative.
It proposes, you approve
No price reaches the shelf without your agreement. The proposal comes from the engine; the decision stays yours.
It holds back when in doubt
Missing purchase cost or too few sales: the engine proposes nothing rather than guess.
Tests under control
Limited audience, stop thresholds, automatic halt as soon as margin slips.
Understand before optimising
The right price holds the balance between incentive and margin.
That balance point is not the same everywhere: buying behaviours do not all react to price with the same intensity. PriXmeur measures that reaction and turns it into comparable scenarios, so the recommendation stays explainable and controllable.
Customer segmentation
Four behaviours, four answers.
SegmentAudienceSensitivityScore
Loyal34%Low0.42
Price-sensitive28%High1.68
Opportunists23%Moderate0.91
Premium15%Very low0.27
Price sensitivity
See the threshold where demand tips over.
High demandLow demand
Low priceRecommended thresholdHigh price
01SegmentGroup comparable behaviours together.
02MeasureEstimate the sensitivity and its uncertainty.
03OptimiseTest the best trade-off for each segment.
04ControlApply the limits and approve the decision.
Built for the trade
From the stall to the decision, without changing your habits.
PriXmeur plugs into your current setup, or becomes your sales interface outright. Stock, batches, purchases and customer behaviour all feed one and the same decision engine.
Connected to your ERP
We synchronise catalogue, stock, batches, sales and customer profiles.
Sales interface included
A straightforward way to publish, sell and track the prices actually applied.
Connected stall4 active signals
TomatoesripeAnalysis running
Avocadosbatch 24Analysis running
Strawberries48 hAnalysis running
Citrusin seasonAnalysis running
Combined ruleSegment + freshness
Proposed price€3.84
Test mode active10% of the audience, automatic halt as soon as margin slipsControlled
Decision engine
Four levers, a single order of priority.
Segment, loyalty, expiry and promotion all run through an explicit order of priority: one single price comes out, and you know which of the four produced it. It is recalculated server-side and stored together with its justification, so every decision can be verified.
01 · SEGMENT
Optimal price per segment
Each segment gets the price that optimises margin, given the sensitivity measured on its buying behaviour.
02 · LOYALTY
Loyalty discount
A loyal segment carries its own discount, applied automatically as soon as a customer is attached to it.
03 · EXPIRY
Markdown as expiry nears
The price falls as the batch’s use-by date approaches: better to sell fresh produce than to lose it.
04 · PROMOTION
Scheduled promotion
A scheduled promotion takes priority over the recommendation, and its effect is compared before publication.
Fraises Gariguette
€5.90 / piece
Rule applied
PROMOTION
Price applied
€4.72 · -20%